fal-ai-media

name	fal-ai-media
description	Video and audio generation via fal.ai MCP. Covers text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). For product or still images use the ai-image-generation skill (OpenAI Image 2 is the canonical SkyyRose engine) — fal.ai image models are not used for product imagery. Use when the user wants to generate videos or audio with AI.
origin	ECC

fal.ai Media Generation

Generate images, videos, and audio using fal.ai models via MCP.

When to Activate

• Creating videos from text or images
• Generating speech, music, or sound effects
• Any video/audio generation task
• User says "create video", "text to speech", "make a video", or similar

Product / still images → use the ai-image-generation skill (OpenAI Image 2 / gpt-image-2, the canonical SkyyRose product-image engine). fal.ai image models (Nano Banana, etc.) are not used here.

MCP Requirement

fal.ai MCP server must be configured. Add to ~/.claude.json:

"fal-ai": {
  "command": "npx",
  "args": ["-y", "fal-ai-mcp-server"],
  "env": { "FAL_KEY": "YOUR_FAL_KEY_HERE" }
}

Get an API key at fal.ai.

MCP Tools

The fal.ai MCP provides these tools:

• search — Find available models by keyword
• find — Get model details and parameters
• generate — Run a model with parameters
• result — Check async generation status
• status — Check job status
• cancel — Cancel a running job
• estimate_cost — Estimate generation cost
• models — List popular models
• upload — Upload files for use as inputs

---

Image Generation → use ai-image-generation

SkyyRose product and still imagery is generated with OpenAI Image 2 (gpt-image-2, high fidelity) via the ai-image-generation skill — the locked canonical engine (project_imagery_engine_oai2), chosen for repeatable, identity-preserving product renders. Do not use fal.ai image models for product imagery. fal.ai's role in this skill is video and audio only (below).

Any paid image generation is gated by STOP-AND-SHOW (Action / SKU / Source / Cost → wait for y); see the ai-image-generation skill for the gate and the belt/gpt-image-2 invocation.

---

Video Generation

Seedance 1.0 Pro (ByteDance)

Best for: text-to-video, image-to-video with high motion quality.

generate(
  model_name: "fal-ai/seedance-1-0-pro",
  input: {
    "prompt": "a drone flyover of a mountain lake at golden hour, cinematic",
    "duration": "5s",
    "aspect_ratio": "16:9",
    "seed": 42
  }
)

Kling Video v3 Pro

Best for: text/image-to-video with native audio generation.

generate(
  model_name: "fal-ai/kling-video/v3/pro",
  input: {
    "prompt": "ocean waves crashing on a rocky coast, dramatic clouds",
    "duration": "5s",
    "aspect_ratio": "16:9"
  }
)

Veo 3 (Google DeepMind)

Best for: video with generated sound, high visual quality.

generate(
  model_name: "fal-ai/veo-3",
  input: {
    "prompt": "a bustling Tokyo street market at night, neon signs, crowd noise",
    "aspect_ratio": "16:9"
  }
)

Image-to-Video

Start from an existing image:

generate(
  model_name: "fal-ai/seedance-1-0-pro",
  input: {
    "prompt": "camera slowly zooms out, gentle wind moves the trees",
    "image_url": "<uploaded_image_url>",
    "duration": "5s"
  }
)

Video Parameters

Param	Type	Options	Notes
prompt	string	required	Describe the video
duration	string	"5s", "10s"	Video length
aspect_ratio	string	"16:9", "9:16", "1:1"	Frame ratio
seed	number	any integer	Reproducibility
image_url	string	URL	Source image for image-to-video

---

Audio Generation

CSM-1B (Conversational Speech)

Text-to-speech with natural, conversational quality.

generate(
  model_name: "fal-ai/csm-1b",
  input: {
    "text": "Hello, welcome to the demo. Let me show you how this works.",
    "speaker_id": 0
  }
)

ThinkSound (Video-to-Audio)

Generate matching audio from video content.

generate(
  model_name: "fal-ai/thinksound",
  input: {
    "video_url": "<video_url>",
    "prompt": "ambient forest sounds with birds chirping"
  }
)

ElevenLabs (via API, no MCP)

For professional voice synthesis, use ElevenLabs directly:

import os
import requests

resp = requests.post(
    "https://api.elevenlabs.io/v1/text-to-speech/<voice_id>",
    headers={
        "xi-api-key": os.environ["ELEVENLABS_API_KEY"],
        "Content-Type": "application/json"
    },
    json={
        "text": "Your text here",
        "model_id": "eleven_turbo_v2_5",
        "voice_settings": {"stability": 0.5, "similarity_boost": 0.75}
    }
)
with open("output.mp3", "wb") as f:
    f.write(resp.content)

VideoDB Generative Audio

If VideoDB is configured, use its generative audio:

# Voice generation
audio = coll.generate_voice(text="Your narration here", voice="alloy")

# Music generation
music = coll.generate_music(prompt="upbeat electronic background music", duration=30)

# Sound effects
sfx = coll.generate_sound_effect(prompt="thunder crack followed by rain")

---

Cost Estimation

Before generating, check estimated cost:

estimate_cost(model_name: "fal-ai/seedance-1-0-pro", input: {...})

Model Discovery

Find models for specific tasks:

search(query: "text to video")
find(model_name: "fal-ai/seedance-1-0-pro")
models()

Tips

• Use seed for reproducible results when iterating on prompts
• Start with shorter durations and lower-cost video models when iterating, then switch to higher-fidelity models for finals
• For video, keep prompts descriptive but concise — focus on motion and scene
• Image-to-video produces more controlled results than pure text-to-video
• Check estimate_cost before running expensive video generations

Related Skills

• videodb — Video processing, editing, and streaming
• video-editing — AI-powered video editing workflows
• content-engine — Content creation for social platforms